super resolution

set up and load the data

path = 'VOCtrainval_06-Nov-2007/VOCdevkit/VOC2007/JPEGImages' path_save = 'VOCtrainval_06-Nov-2007/VOCdevkit/VOC2007/converted'

all_dir = glob.glob(path + '/*.jpg')

for filename in all_dir: img = cv2.imread(filename) img_y2 = img.resize(288) img_y2.save(path_save+'/y_large/'+(filename[len(filename)-10:])) img_y = img.resize(144) img_y.save(path_save+'/y_mid/'+(filename[len(filename)-10:])) img_x = img.resize(72) img_x.save(path_save+'/x/'+(filename[len(filename)-10:]))

some examples of the data

main function for the model

all model by step and there results

i choose to train the model from step 3. for that i increase the number of epochs